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Record W2909456170 · doi:10.1029/2018ja025476

Simulation and Observation of Lunar Tide Effect on High‐Latitude, Mesospheric and Lower Thermospheric Winds During the 2013 Sudden Stratospheric Warming Event

2019· article· en· W2909456170 on OpenAlexafffund
Qian Wu, W. E. Ward, Sam Kristoffersen, Astrid Maute, Jing Liu

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of New Brunswick
FundersDivision of Atmospheric and Geospace SciencesNatural Sciences and Engineering Research Council of CanadaNational Science Foundation of Sri LankaCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaNational Aeronautics and Space AdministrationCanadian Space AgencyNational Science Foundation
KeywordsThermosphereAtmospheric tideAtmospheric sciencesMesosphereForcing (mathematics)Sudden stratospheric warmingMiddle latitudesClimatologyEnvironmental scienceAmplitudeStratosphereLatitudeIonosphereGCM transcription factorsAtmosphere (unit)GeologyGeneral Circulation ModelMeteorologyClimate changePolar vortexGeophysicsPhysicsOceanographyGeodesy

Abstract

fetched live from OpenAlex

Abstract We investigate the high‐latitude mesospheric and lower thermospheric winds during the 2013 sudden stratospheric warming event using ground‐based optical Doppler remote sensing observations of the OH and O (557.7 nm) emission from Eureka (80°N, 86°W) and Thermosphere Ionosphere Mesosphere Electrodynamics‐General Circulation Model (TIME‐GCM) simulations. Simulations with and without lunar tidal forcing of the TIME‐GCM were performed. It has been found that the additional lunar tidal forcing only impacts slightly the semidiurnal tidal amplitude and phase at Eureka. The TIME‐GCM simulations still have noticeable discrepancies in the mean winds and the semidiurnal tidal amplitude and phase compared to the observations. The semidiurnal tidal phase shift during the stratospheric warming event may be associated with the sudden stratospheric warming related zonal mean wind reversal, which is similar to the seasonal change in the zonal mean wind from winter to summer. Accordingly, during the reversal, more modes of the semidiurnal tide propagate to the mesosphere, changing the phase of the semidiurnal tide.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.444
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.288
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2019
Admission routes2
Has abstractyes

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